Climate Classification

Contour map

Photo by Visit Greenland on Unsplash

Aasiaat, Greenland during winter

How do you find America? Turn left at Greenland…
— Ringo Starr, media question to Beatles during first U.S. tour 1964

Ingest

map attributes with climate zones

df <- read.csv("archetypes/climate-classification/world-climates-koppen-geiger.csv", header = TRUE, stringsAsFactors = FALSE)
head(df, n=10)

unique(df$climates_f)

##  [1] "ET"  "EF"  ""    "Dfd" "Dfc" "Dsc" "Dsd" "Bsk" "Cfc" "Dwd" "Cfb" "Csc"
## [13] "Dfb" "Dwc" "Dwb" "Dsb" "CSb" "Dfa" "Bwk" "Dwa" "Csa" "Cfa" "Dsa" "Cwa"
## [25] "BSh" "BWh" "Cwb" "Cwc" "Am"  "AW"  "As"  "Af"

Base Map

Köppen-Geiger Climate Zones

climate_zone_map <- st_read("archetypes/climate-classification/world-climates-koppen-geiger.geojson")

## Reading layer `world-climates-koppen-geiger' from data source 
##   `C:\Users\jaybe\Desktop\kamino-dev\sources\10-maps\2-area\4-contour\archetypes\climate-classification\world-climates-koppen-geiger.geojson' 
##   using driver `GeoJSON'
## Simple feature collection with 25143 features and 2 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -180 ymin: -90 xmax: 180 ymax: 90
## Geodetic CRS:  WGS 84

Wrangle

enrich climate zone labels

climate_zone_map_enriched <-
  climate_zone_map %>% 
  mutate(
    main = case_when(
      str_detect(climates_f, "^A") ~ "Equatorial climates",
      str_detect(climates_f, "^B") ~ "Arid climates",
      str_detect(climates_f, "^C") ~ "Warm temperate climates",
      str_detect(climates_f, "^D") ~ "Snow climates",
      str_detect(climates_f, "^E") ~ "Polar climates",
      TRUE ~ NA_character_
    ),
    type = case_when(
      str_detect(climates_f, "^Af") ~ "Equatorial rainforest, fully humid",
      str_detect(climates_f, "^Am") ~ "Equatorial monsoon",
      str_detect(climates_f, "^As") ~ "Equatorial savannah with dry summer",
      str_detect(climates_f, "^AW") ~ "Equatorial savannah with dry winter",
      str_detect(climates_f, "^BS") ~ "Arid steppe climate",
      str_detect(climates_f, "^Bs") ~ "Arid steppe climate",
      str_detect(climates_f, "^BW") ~ "Arid desert climate",
      str_detect(climates_f, "^Bw") ~ "Arid desert climate",
      str_detect(climates_f, "^CS") ~ "Warm temperate climate with dry summer",
      str_detect(climates_f, "^Cs") ~ "Warm temperate climate with dry summer",
      str_detect(climates_f, "^Cw") ~ "Warm temperate climate with dry winter",
      str_detect(climates_f, "^Cf") ~ "Warm temperate climate, fully humid",
      str_detect(climates_f, "^Ds") ~ "Snow climate with dry summer",
      str_detect(climates_f, "^Dw") ~ "Snow climate with dry winter",
      str_detect(climates_f, "^Df") ~ "Snow climate, fully humid",
      str_detect(climates_f, "ET") ~ "Polar tundra climate",
      str_detect(climates_f, "EF") ~ "Polar frost climate",
      TRUE ~ NA_character_
    ),
    type = factor(type, levels = c(
      "Equatorial rainforest, fully humid",
      "Equatorial monsoon",
      "Equatorial savannah with dry summer",
      "Equatorial savannah with dry winter",
      "Arid steppe climate",
      "Arid desert climate",
      "Warm temperate climate with dry summer",
      "Warm temperate climate with dry winter",
      "Warm temperate climate, fully humid",
      "Snow climate with dry summer",
      "Snow climate with dry winter",
      "Snow climate, fully humid",
      "Polar tundra climate",
      "Polar frost climate",
      TRUE ~ NA_character_
    ))
  ) %>% 
  filter(!is.na(type))

climate_zone_map_enriched

Plot

contour

theme_opts <- theme(
  text = element_text(family = "inconsolata", size = 12), 
  plot.title = element_text(color = "black", size = 16, face = "bold"),
  plot.subtitle = element_text(color = "black", size = 12),
  plot.caption = element_text(color = "#555555", size = 11),
  plot.background = element_rect(fill = "#f0f0f0", color = NA),
  plot.margin = margin(.25, .25, .25, .25, "cm"),
  axis.title.x = element_blank(),
  axis.title.y = element_blank(),
  axis.text.x = element_blank(),
  axis.text.y = element_blank(),
  panel.border = element_blank(),
  panel.background = element_rect(fill = "#f0f0f0", color = NA),
  # panel.grid.minor = element_blank(),
  # panel.grid.major = element_blank(),
  legend.position = 'bottom',
  legend.title = element_blank(), #change legend title font size
  legend.text = element_text(size=10)
)

fill_palette <- c(
  "#4f3314",
  "#784e1e",
  "#a16928",
  "#ca8432",
  "#ca9273",
  "#d8af98",
  "#e7daae",
  "#dbd787",
  "#cbcf60",
  "#b6ccca",
  "#98b7b4",
  "#7aa29e",
  "#36b9cd",
  "#2890a0"
)

color_palette <- darken(fill_palette, 0.1)

v1 = ggplot(data = climate_zone_map_enriched) + 
  geom_sf(aes(fill=type, color=type), stroke=0.5) +
  scale_fill_manual( values = fill_palette ) +
  scale_color_manual( values = color_palette ) +
  coord_sf() +
  ggtitle( "Köppen-Geiger Climate Zones" ) +
  theme_void() +
  theme_opts

girafe( ggobj = v1, width_svg = 16, height_svg = 9,
  options = list( opts_sizing(rescale = TRUE, width = 1.0) )
)

References

citations for narrative and data sources

Narrative: inspired by visualization created by Cédric Scherer
Map Source: Kottek et al. 2006 (DOI: 10.1127/0941-2948/2006/0130)

Based on raster file from:
Kottek, M., J. Grieser, C. Beck, B. Rudolf, and F. Rubel, 
2006: World Map of the Koppen-Geiger climate classification updated. 
Meteorol. Z., 15, 259-263. 
DOI: 10.1127/0941-2948/2006/0130.